Commentary: Attacking Biology’s Complexity with New Genomics Approaches

January 8, 2019, 9:17 PM UTC

Our founding thesis at Illumina was straightforward: biology is extremely complex and to unravel that biology, and thereby dramatically impact human medicine, would require a much larger scale of experimentation at an exponentially cheaper cost per experiment. And it worked, sort of.

For 20 years, Illumina has powered the genomics revolution through dramatic miniaturization and multiplexed assay development. First with arrays, and now with next-generation sequencing, experiments are conducted on the nanometer scale with billions of assays occurring in parallel. Those tools, and their applications, created the promise of personalized medicine and are revolutionizing entire areas of medical practice.

Non-invasive prenatal testing was introduced in late 2011, and only 6 years later more than 2 million tests are run annually. Sequencing of tumors, either via biopsy or through cell-free analysis, is changing cancer diagnosis and treatment. Enough so that 2018 saw the first initial drug approval for therapeutic usage based on tumor genetic signature (NTRK gene fusion) rather than the traditional delineation of cancer origin (lung, colon, etc).

Still however, two decades later, the promise of personalized medicine is primarily just that, a promise. Biology remains very complex. It seems that every time we unravel a portion of that complexity, we uncover more complexity.

As we start to understand a particular gene’s function, we then need to understand that gene’s networks, its post-translational modifications at the RNA and protein level, and its complex cellular regulation, before we can even get to the question we want to ask: how all of that impacts disease.

Reducing the sequencing cost for a whole human genome from more than $1 billion to under $1,000 has driven enormous progress on this very incomplete puzzle. Reducing it to $100 will generate additional discoveries; however, those discoveries will be incremental, not revolutionary. Scientists require orthogonal approaches and novel capabilities in the tools they use to catapult forward our knowledge base. We believe that two approaches fit this criteria: dramatic improvement in resolution, and the integration of previously disparate disciplines and capabilities.

A Resolution Revolution: Single Cell Genomics

Until very recently, genomics had relied on the analysis of bulk tissue samples. While important questions were answered, bulk analysis ignores critical biological information. Any biopsy is comprised of a variety of cell types.

More than 200 human cell types are known (and counting). Blending all of the cells of a sample together for bulk analysis obscures function at the cellular level and ignores proportional differences in cell types. With this type of analysis, we are only able to reveal the most obvious information. Single-cell genomics – the ability to analyze each cell individually on a genome-wide scale – is now providing the lens needed to match biological complexity.

10x Genomics (and others) are pioneering single-cell genomics approaches and expanding the types of analysis possible on the single cell level, including DNA sequencing, RNA profiling, epigenetic discovery, and immunology. More and more applications of single cell analysis will be developed now that this important platform has become robust and its usage is proliferating across the research ecosystem.

The cellular level insights from single-cell genomics are really just starting to demonstrate the power of this approach; for instance, the identification of a rare airway cell type (pulmonary ionocyte) now deemed to be important in cystic fibrosis.

That said, there is even another dimension of information to augment these experiments – how these cells are positioned and interact in the tissue. This spatial information will be vital to understanding some diseases.

Traditionally, the analysis of tissue has been the domain of pathology – thin slices stained with one or two markers. An important future area of tool development will bring genomic-level analysis to tissue with intact spatial positioning of cells, thereby allowing genomic assays to be run on cells at the tissue level.

The Power of Integration

While the idea of integrating DNA, RNA and protein data has been talked about for over a decade, this data has suffered from both a lack of resolution as well as unifying assay technology. However, recent advances are overcoming these limitations; it is now possible to analyze, at the single-cell level in the same sample, both RNA transcription and epigenetic changes, providing an insight into how epigenetics affects transcription.

Likewise, one can determine both the antigen and the sequence of the specific immune receptor to which the antigen binds with single-cell discrimination, opening up the opportunity for immune mapping, future therapeutics and universal diagnostic tests.

Soon, integration will expand beyond these multi-analyte biological “read only” assays, to incorporate powerful biological “writing” capabilities such as CRISPR. Integration of CRISPR with genomic tools and single-cell analysis will allow scientists to write (edit DNA), test (assay for some biological output), and read (sequence) in a parallel fashion, interrogating multiple readouts (DNA, RNA, protein, phenotype).

An early example of this integration is Perturb-SEQ, where, in a multiplexed assay, tens of thousands of individual genes are disrupted in single cells with the phenotypic results of that disruption being analyzed through single-cell RNA profiling, enabling comprehensive functional genomics.

The next step in this integration will be to write uniquely at 10,000s of different locations in single cells, then test for phenotypic change, including changes in gene expression through single-cell RNA profiling.

To date, biological writing has been an expensive and manually laborious process confined to large-scale efforts. However, desktop instruments are in development for single-cell, multiplexed CRISPR editing to enable researchers to integrate single-cell DNA reading and writing. We will soon appreciate the power of integrating DNA reading and writing in a closed loop system and the dramatically faster pace of learning that will result.

These novel approaches will drive crucial and exciting progress in medicine, while underscoring the continued enormity of the scale of biological complexity. The opportunities and advances of the next 20 years will undoubtedly be even more exciting than the last.

John Stuelpnagel is a co-founder of both Illumina and Ariosa Diagnostics. Additionally, he currently serves as Chairman of the Board of Directors of 10X Genomics. Bryan Roberts is a partner at Venrock.

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